First-principles study of oxygenates on Co surfaces in Fischer-Tropsch synthesis

Extensive density function theory calculations are performed to study the mechanism of the formation of aldehyde and alcohol on Co surfaces in Fischer-Tropsch synthesis, a challenging issue in heterogeneous catalysis. Three possible pathways for the production of formaldehyde and methanol on flat and stepped Co(0001) surfaces are investigated: (i) CO + 4H -> CHO + 3H -> CH2O + 2H -> CH3O + H -> CH3OH; (ii) CO + 4H -> COH + 3H -> CHOH + 2H -> CH2OH + H -> CH3OH; and (iii) the coupling reactions of CH2 + O -> CH2O and CH3 + OH -> CH3OH. It is found that these pathways are generally favored at step sites, and the preferred mechanism is pathway (i) via CHO. Furthermore, the three traditional chain growth mechanisms in Fischer-Tropsch synthesis are semi quantitatively compared and discussed. Our results suggest that the two mechanisms involving oxygenate intermediates (the CO-insertion and hydroxycarbene mechanisms) are less important than the carbene mechanism in the production of long chain hydrocarbons. However, the CO-insertion mechanism may be responsible for the production of long-chain oxygenates.

General trends in CO dissociation on transition metal surfaces

Dissociative adsorption is one of the most important reactions in catalysis. In this communication we propose a model aiming to generalize the important factors that affect dissociation reactions. Specifically, for a dissociation reaction, say AB -->A + B, the model connects the dissociation barrier with the association barrier, the chemisorption energies of A and B at the final state and the bonding energy of AB in the gas phase. To apply this model, we have calculated CO dissociation on Ru(0001), Rh(111), Pd(111) (4d transition metals), Os(0001), Ir(111), and Pt(111) (5d transition metals) using density function theory (DFT). All the barriers are determined. We find that the DFT results can be rationalized within the model. The model can also be used to explain many experimental observations. (C) 2001 American Institute of Physics.

Incorporating Higher Moments into Value at Risk Forecasting

Value-at-risk (VaR) forecasting generally relies on a parametric density function of portfolio returns that ignores higher moments or assumes them constant. In this paper, we propose a simple approach to forecasting of a portfolio VaR. We employ the Gram-Charlier expansion (GCE) augmenting the standard normal distribution with the first four moments, which are allowed to vary over time. In an extensive empirical study, we compare the GCE approach to other models of VaR forecasting and conclude that it provides accurate and robust estimates of the realized VaR. In spite of its simplicity, on our dataset GCE outperforms other estimates that are generated by both constant and time-varying higher-moments models.

Modeling Multivariate Interest Rates Using Time-Varying Copulas and Reducible Nonlinear Stochastic Differential Equations

We propose a new approach for modeling nonlinear multivariate interest rate processes based on time-varying copulas and reducible stochastic differential equations (SDEs). In the modeling of the marginal processes, we consider a class of nonlinear SDEs that are reducible to Ornstein--Uhlenbeck (OU) process or Cox, Ingersoll, and Ross (1985) (CIR) process. The reducibility is achieved via a nonlinear transformation function. The main advantage of this approach is that these SDEs can account for nonlinear features, observed in short-term interest rate series, while at the same time leading to exact discretization and closed-form likelihood functions. Although a rich set of specifications may be entertained, our exposition focuses on a couple of nonlinear constant elasticity volatility (CEV) processes, denoted as OU-CEV and CIR-CEV, respectively. These two processes encompass a number of existing models that have closed-form likelihood functions. The transition density, the conditional distribution function, and the steady-state density function are derived in closed form as well as the conditional and unconditional moments for both processes. In order to obtain a more flexible functional form over time, we allow the transformation function to be time varying. Results from our study of U.S. and UK short-term interest rates suggest that the new models outperform existing parametric models with closed-form likelihood functions. We also find the time-varying effects in the transformation functions statistically significant. To examine the joint behavior of interest rate series, we propose flexible nonlinear multivariate models by joining univariate nonlinear processes via appropriate copulas. We study the conditional dependence structure of the two rates using Patton (2006a) time-varying symmetrized Joe--Clayton copula. We find evidence of asymmetric dependence between the two rates, and that the level of dependence is positively related to the level of the two rates. (JEL: C13, C32, G12) Copyright The Author 2010. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oxfordjournals.org, Oxford University Press.

Anisotropic seismic inversion using a multigrid Monte Carlo approach

We propose a new approach for the inversion of anisotropic P-wave data based on Monte Carlo methods combined with a multigrid approach. Simulated annealing facilitates objective minimization of the functional characterizing the misfit between observed and predicted traveltimes, as controlled by the Thomsen anisotropy parameters (epsilon, delta). Cycling between finer and coarser grids enhances the computational efficiency of the inversion process, thus accelerating the convergence of the solution while acting as a regularization technique of the inverse problem. Multigrid perturbation samples the probability density function without the requirements for the user to adjust tuning parameters. This increases the probability that the preferred global, rather than a poor local, minimum is attained. Undertaking multigrid refinement and Monte Carlo search in parallel produces more robust convergence than does the initially more intuitive approach of completing them sequentially. We demonstrate the usefulness of the new multigrid Monte Carlo (MGMC) scheme by applying it to (a) synthetic, noise-contaminated data reflecting an isotropic subsurface of constant slowness, horizontally layered geologic media and discrete subsurface anomalies; and (b) a crosshole seismic data set acquired by previous authors at the Reskajeage test site in Cornwall, UK. Inverted distributions of slowness (s) and the Thomson anisotropy parameters (epsilon, delta) compare favourably with those obtained previously using a popular matrix-based method. Reconstruction of the Thomsen epsilon parameter is particularly robust compared to that of slowness and the Thomsen delta parameter, even in the face of complex subsurface anomalies. The Thomsen epsilon and delta parameters have enhanced sensitivities to bulk-fabric and fracture-based anisotropies in the TI medium at Reskajeage. Because reconstruction of slowness (s) is intimately linked to that epsilon and delta in the MGMC scheme, inverted images of phase velocity reflect the integrated effects of these two modes of anisotropy. The new MGMC technique thus promises to facilitate rapid inversion of crosshole P-wave data for seismic slownesses and the Thomsen anisotropy parameters, with minimal user input in the inversion process.

Distribution of the Demmel Condition Number of Wishart Matrices

This paper studies the Demmel condition number of Wishart matrices, a quantity which has numerous applications to wireless communications, such as adaptive switching between beamforming and diversity coding, link adaptation, and spectrum sensing. For complex Wishart matrices, we give an exact analytical expression for the probability density function (p.d.f.) of the Demmel condition number, and also derive simplified expressions for the high tail regime. These results indicate that the condition of complex Wishart matrices is dominantly decided by the difference between the matrix dimension and degree of freedom (DoF), i.e., the probability of drawing a highly ill conditioned matrix decreases considerably when the difference between the matrix dimension and DoF increases. We further investigate real Wishart matrices, and derive new expressions for the p.d.f. of the smallest eigenvalue, when the difference between the matrix dimension and DoF is odd. Based on these results, we succeed to obtain an exact p.d.f. expression for the Demmel condition number, and simplified expressions for the high tail regime.

Mapping piezoelectric nonlinearity in the Rayleigh regime using band excitation piezoresponse force microscopy

Band excitation piezoresponse force microscopy enables local investigation of the nonlinear piezoelectric behavior of ferroelectric thin films. However, the presence of additional nonlinearity associated with the dynamic resonant response of the tip-surface junction can complicate the study of a material's nonlinearity. Here, the relative importance of the two nonlinearity sources was examined as a function of the excitation function. It was found that in order to minimize the effects of nonlinear tip-surface interactions but achieve good signal to noise level, an optimal excitation function must be used. (C) 2011 American Institute of Physics. [doi: 10.1063/1.3593138]

Nakagami-m Phase Model: Further Results and Validation

This paper contributes to and expands on the Nakagami-m phase model. It derives exact, closed-form expressions for both the phase cumulative distribution function and its inverse. In addition, empirical first- and second-order statistics obtained from measurements conducted in a body-area network scenario were used to fit the phase probability density function, the phase cumulative distribution function, and the phase crossing rate expressions. Remarkably, the unlikely shapes of the phase statistics, as predicted by the theoretical formulations, are actually encountered in practice.

Ergodic Capacity of Cognitive TAS/GSC Relaying in Nakagami-m Fading Channels

We examine the impact of transmit antenna selection with receive generalized selection combining (TAS/GSC) for cognitive decode-and-forward (DF) relaying in Nakagami-m fading channels. We select a single transmit antenna at the secondary transmitter which maximizes the receive signal-to-noise ratio (SNR) and combine a subset of receive antennas with the largest SNRs at the secondary receiver. In an effort to assess the performance, we first derive the probability density function and cumulative distribution function of the end-to-end SNR using the moment generating function. We then derive new exact closed-form expression for the ergodic capacity. More importantly, by deriving the asymptotic expression for the high SNR approximation of the ergodic capacity, we gather deep insights into the high SNR slope and the power offset. Our results show that the high SNR slope is 1/2 under the proportional interference power constraint. Under the fixed interference power constraint, the high SNR slope is zero.

Integrating Multiple Point Statistics with Aerial Geophysical Data to assist Groundwater Flow Models

The process of accounting for heterogeneity has made significant advances in statistical research, primarily in the framework of stochastic analysis and the development of multiple-point statistics (MPS). Among MPS techniques, the direct sampling (DS) method is tested to determine its ability to delineate heterogeneity from aerial magnetics data in a regional sandstone aquifer intruded by low-permeability volcanic dykes in Northern Ireland, UK. The use of two two-dimensional bivariate training images aids in creating spatial probability distributions of heterogeneities of hydrogeological interest, despite relatively ‘noisy’ magnetics data (i.e. including hydrogeologically irrelevant urban noise and regional geologic effects). These distributions are incorporated into a hierarchy system where previously published density function and upscaling methods are applied to derive regional distributions of equivalent hydraulic conductivity tensor K. Several K models, as determined by several stochastic realisations of MPS dyke locations, are computed within groundwater flow models and evaluated by comparing modelled heads with field observations. Results show a significant improvement in model calibration when compared to a simplistic homogeneous and isotropic aquifer model that does not account for the dyke occurrence evidenced by airborne magnetic data. The best model is obtained when normal and reverse polarity dykes are computed separately within MPS simulations and when a probability threshold of 0.7 is applied. The presented stochastic approach also provides improvement when compared to a previously published deterministic anisotropic model based on the unprocessed (i.e. noisy) airborne magnetics. This demonstrates the potential of coupling MPS to airborne geophysical data for regional groundwater modelling.

Shadowed fading in body–to–body communications channels in an outdoor environment at 2.45 GHz

In this paper a number of outdoor body-to-body communications channels at 2.45 GHz which are deemed to be susceptible to shadowed fading are analyzed. The newlyproposed shadowed K-Il model is used to characterize thesechannels. Its probability density function is shown to provide an improved fit to the distribution of the signal fading compared to established models such as lognormal, Nakagamiand Rice.

Human body shadowing in cellular device-to-device communications: channel modeling using the shadowed κ−μ fading model

Using device-to-device communications as an underlay for cellular communications will provide an exciting opportunity to increase network capacity as well as improving spectral efficiency. The unique geometry of device-to-device links, where user equipment is often held or carried at low elevation and in close proximity to the human body, will mean that they are particularly susceptible to shadowing events caused not only by the local environment but also by the user's body. In this paper, the shadowed κ - μ fading model is proposed, which is capable of characterizing shadowed fading in wireless communication channels. In this model, the statistics of the received signal are manifested by the clustering of multipath components. Within each of these clusters, a dominant signal component with arbitrary power may exist. The resultant dominant signal component, which is formed by the phasor addition of these leading contributions, is assumed to follow a Nakagami- m distribution. The probability density function, moments, and the moment-generating function are also derived. The new model is then applied to device-to-device links operating at 868 MHz in an outdoor urban environment. It was found that shadowing of the resultant dominant component can vary significantly depending upon the position of the user equipment relative to the body and the link geometry. Overall, the shadowed κ - μ fading model is shown to provide a good fit to the field data as well as providing a useful insight into the characteristics of the received signal.

Distribution of terminal nerve entry points to the flexor and extensor groups of forearm muscles:An anatomical study

The motor points of the skeletal muscles, mainly of interest to anatomists and physiologists, have recently attracted much attention from researchers in the field of functional electrical stimulation. The muscle motor point has been defined as the entry point of the motor nerve branch into the epimysium of the muscle belly. Anatomists have pointed out that many muscles in the limbs have multiple motor points. Knowledge of the location of nerve branches and terminal nerve entry points facilitates the exact insertion and the suitable selection of the number of electrodes required for each muscle for functional electrical stimulation. The present work therefore aimed to describe the number, location, and distribution of motor points in the human forearm muscles to obtain optimal hand function in many clinical situations. Twenty three adult human cadaveric forearms were dissected. The numbers of primary nerves and motor points for each muscle were tabulated. The mean numbers and the standard deviation were calculated and grouped in tables. Data analyses were performed with the use of a statistical analysis package (SPSS 13.0). The proximal third of the muscle was the usual part of the muscle that received the motor points. Most of the forearm muscles were innervated from the lateral side and deep surface of the muscle. The information in this study may also be usefully applied in selective denervation procedures to balance muscles in spastic upper limbs. Copyright © 2007 Via Medica.

Stochastic Analysis of Saltwater Intrusion in Heterogeneous Aquifers using Local Average Subdivision

This study investigates the effects of ground heterogeneity, considering permeability as a random variable, on an intruding SW wedge using Monte Carlo simulations. Random permeability fields were generated, using the method of Local Average Subdivision (LAS), based on a lognormal probability density function. The LAS method allows the creation of spatially correlated random fields, generated using coefficients of variation (COV) and horizontal and vertical scales of fluctuation (SOF). The numerical modelling code SUTRA was employed to solve the coupled flow and transport problem. The well-defined 2D dispersive Henry problem was used as the test case for the method. The intruding SW wedge is defined by two key parameters, the toe penetration length (TL) and the width of mixing zone (WMZ). These parameters were compared to the results of a homogeneous case simulated using effective permeability values. The simulation results revealed: (1) an increase in COV resulted in a seaward movement of TL; (2) the WMZ extended with increasing COV; (3) a general increase in horizontal and vertical SOF produced a seaward movement of TL, with the WMZ increasing slightly; (4) as the anisotropic ratio increased the TL intruded further inland and the WMZ reduced in size. The results show that for large values of COV, effective permeability parameters are inadequate at reproducing the effects of heterogeneity on SW intrusion.

Effective grain size distribution analysis for interpretation of tidal-deltaic facies: West Bengal Sundarbans

Research over the past two decades on the Holocene sediments from the tide dominated west side of the lower Ganges delta has focussed on constraining the sedimentary environment through grain size distributions (GSD). GSD has traditionally been assessed through the use of probability density function (PDF) methods (e.g. log-normal, log skew-Laplace functions), but these approaches do not acknowledge the compositional nature of the data, which may compromise outcomes in lithofacies interpretations. The use of PDF approaches in GSD analysis poses a series of challenges for the development of lithofacies models, such as equifinal distribution coefficients and obscuring the empirical data variability. In this study a methodological framework for characterising GSD is presented through compositional data analysis (CODA) plus a multivariate statistical framework. This provides a statistically robust analysis of the fine tidal estuary sediments from the West Bengal Sundarbans, relative to alternative PDF approaches.